Abstract
It is well known that inference methods for i.i.d. data or, more generally, independent data are simply not consistent when the underlying sequence is dependent. Therefore, the resampling and subsampling methods discussed in the previous chapters need to be modified to be applicable with time series data.
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© 1999 Springer Science+Business Media New York
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Politis, D.N., Romano, J.P., Wolf, M. (1999). Subsampling for Stationary Time Series. In: Subsampling. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4612-1554-7_3
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DOI: https://doi.org/10.1007/978-1-4612-1554-7_3
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4612-7190-1
Online ISBN: 978-1-4612-1554-7
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